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Transport is an important source of air pollution and greenhouse gas emissions. Although the applications of information and communication technologies (ICTs) for transport, also known as intelligent transport systems, are seen as having great potential to help reduce emissions from road transport, their exact impact on CO2 emissions are uncertain for decision makers from government to industry. This uncertainty hinders the deployment of such applications. Therefore there is a need for a common evaluation approach to assess the CO2 impact of ICT measures in a systemic and realistic way. In this study, a methodology framework to evaluate the impact of ICT measures on CO2 emissions is explained. The methodology was developed within the European Union FP7 project Amitran. In particular, this study focuses on the outline and the framework architecture of the methodology as well as the required interfaces between the required models. The use of the methodology is demonstrated by applying it to a use case of dynamic traffic light systems. Finally, the efforts made to validate the methodology and make it accessible to users are explained.

Les réseaux de distribution d'électricité sont depuis plusieurs années au cœur des évolutions énergétiques et environnementales qui touchent nos sociétés. Les clients délaissent progressivement les chauffe-eaux instantanés à gaz pour les ballons d'eau chaude électriques, ainsi que les voitures diesel pour les véhicules électriques. D'autre part, la production d'énergie renouvelable commence à constituer une part importante du mix énergétique mais ne concorde pas nécessairement avec la consommation électrique des usagers. Elle peut donc être refoulée vers le reste du réseau de distribution, voire le réseau de transport. Toutes ces évolutions doivent être maîtrisées pour éviter un renforcement conséquent des infrastructures du réseau, et limiter les répercussions économiques et environnementales de la transition énergétique. Dans ce sens, ces travaux de thèse portent sur la supervision énergétique des réseaux de distribution HTA, en particulier de type rural et péri-urbain, afin d'y encourager la consommation locale des énergies renouvelables et d'optimiser le coût d'acheminement d'énergie pour les gestionnaires du réseau. Les algorithmes développés visent principalement à piloter les charges tels que les véhicules électriques et les ballons d'eau chaude sanitaire raccordés au réseau de distribution. Le système de supervision agit au niveau d'un poste source HTB/HTA et utilise les mesures ainsi que les prévisions de production et de consommation d'énergie afin de piloter les différentes charges disponibles. La stratégie proposée prend aussi en compte les contraintes électriques qui peuvent apparaître sur le réseau à travers une approche de co-simulation entre les logiciels Matlab/Simulink, où la supervision est implémentée, et DIgSILENT PowerFactory, où le réseau de distribution est finement modélisé. Les consignes de supervision sont donc testées et adaptées en temps-réel avant d'être envoyées aux différents utilisateurs. Enfin, le pilotage des producteurs décentralisés est aussi utilisé comme levier supplémentaire pour résoudre une partie des contraintes électriques. Electricity distribution grids have been for several years at the heart of energy and environmental challenges affecting our societies. Customers are increasingly switching from instantaneous gas water heaters to electric hot water tanks, and from diesel cars to electric vehicles. On the other hand, renewable energy production is starting to become an important part of the energy mix but does not necessarily match the electricity consumption of the users. It can therefore be transmitted to the rest of the distribution network, and eventually the transmission network. All these evolutions must be controlled to avoid significant reinforcements of the network infrastructures and limit the economic and environmental impacts of the energy transition. In this context, this thesis focuses on the energy supervision of medium voltage distribution grids, particularly rural and suburban types, to promote the local consumption of renewable energy and optimize energy transmission costs for network operators. The developed algorithms mainly aim to control loads such as electric vehicles and electric water heaters. The supervision system acts at the level of an HV/MV substation and uses real-time production and consumption measurements as well as day-ahead forecasts to control the various available loads. The proposed strategy also takes into account the electrical constraints that can appear on the network through a co-simulation approach between Matlab/Simulink software, where the supervision strategy is implemented, and DIgSILENT PowerFactory, where the distribution network is finely modeled. The supervision's power set-points are therefore tested and adapted in real-time before being sent to the various customers. Finally, the control of decentralized producers is used as an additional lever to solve a part of the detected electrical constraints.

This paper has presented the estimation methodology of the quick charging station for electric vehicles (EVs) based on both area and population density data. The proportion of EV owners per number of population in location data; is also used to compute the number of the quick charging stations. The population density data and proportion of EVs owners per number of population in area data are varied from 1 to 6 % and 0.01 to 0.8 %, respectively. The simulation results showed that the number of EVs stations increased and the randomly selected Feeder No.1 was installed at EVs stations; of which range from No.1 to No.4. The total real power loss increased up to 18%. Therefore, this study could be verified that the quick charging stations should be considered both optimal in sizing and location of EVs charging stations.

Abstract Cost-effectively decarbonising the power sector and household energy use using variable renewable energy will require that electricity consumption becomes much more flexible and responsive to constraints in supply and the distribution network. In recent years residential demand response (DR) has received increasing attention that has sought to answer, based on current evidence, questions about how much consumers will engage with DR. This paper critically reviews the evidence base for residential consumer engagement with DR and draws out several important limitations in it. We argue for a more action-oriented focus on developing practical strategies to enable and unlock greater loadshifting and consumer engagement with DR within a changing technology and regulatory context. A number of recommendations are put forward for accelerating UK consumer engagement with DR, presented under three broad strategies: (a) promote awareness of smart tariffs, smart meters and storage and automation behind-the-meter devices as mutually-supportive components within a common ‘DR technology cluster’; (b) deliver targeted support for adoption of electric vehicles and other storage and automation technologies; (c) enable and support informed adoption of DR-enabling products and services through ‘smarter’ digital comparison tools (DCTs), data portability, and faster, simpler switching. The interdependency between components within this DR technology cluster delivers efficiency but also poses a risk that one delayed component (e.g., smart metering) will hold-up policy and industry support for other components. The urgency of decarbonisation goals makes it necessary to push forward as many of these elements as possible rather than the pace being set by the slowest.

AbstractAccelerated warming and melting of Arctic sea-ice has been associated with significant increases in phytoplankton productivity in recent years. Here, utilizing a multiproxy approach, we reconstruct an annually resolved record of Labrador Sea productivity related to sea-ice variability in Labrador, Canada that extends well into the Little Ice Age (LIA; 1646 AD). Barium-to-calcium ratios (Ba/Ca) and carbon isotopes (δ13C) measured in long-lived coralline algae demonstrate significant correlations to both observational and proxy records of sea-ice variability, and show persistent patterns of co-variability broadly consistent with the timing and phasing of the Atlantic Multidecadal Oscillation (AMO). Results indicate reduced productivity in the Subarctic Northwest Atlantic associated with AMO cool phases during the LIA, followed by a step-wise increase from 1910 to present levels—unprecedented in the last 363 years. Increasing phytoplankton productivity is expected to fundamentally alter marine ecosystems as warming and freshening is projected to intensify over the coming century.

The combination of car-sharing and electric vehicles can increase the acceptance of electric vehicles and facilitate car-sharing to be a more sustainable means of transport. However, this also poses more challenges for the good planning of electric car-sharing systems. To assist car-sharing companies in improving the planning decisions, this paper developed an evaluation framework from a comprehensive view. In the first step, four evaluation criteria were identified according to the planning process: construction of stations; routine inspection; vehicle usability and relocation management; and the maintenance and replacement of stations. Then, a combinatorial method based on analytic hierarchy process (AHP), cost-benefit analysis (CBA), and Voronoi diagram (VD) is developed to determine the relative weight of the four criteria and evaluate the alternative. Finally, the evaluation framework was applied in a realistic case of EVCARD, which is the most influential electric car-sharing company in China. The performance of two different operational districts of EVCARD—Jingan and Changning—were compared. The results showed that vehicle usability and relocation management is the greatest criterion influencing the planning performance of the electric car-sharing system in China, and that routine inspection is a negligible but important factor. According to the relative scores, Jiagan District performed better than Changning district.

In recent years, a ban on short-haul flights for which alternative, more environmentally friendly transportation is available has been on European regulatory agendas, particularly in countries like Germany, with its well-developed high-speed rail (HSR) and a dense network of low-cost, point-to-point airline traffic. This study aims to quantify the potential impact on CO2 emissions of substituting short-haul flights with rail frequencies in 87 German air travel corridors. Using OAG data on passenger bookings and airline schedules for 2019, as well as current rail travel times, we determine the target flights by looking at the actual proportion of connecting passengers per frequency. We estimate a potential reduction in CO2 emissions of between 2.7% and 22%, depending on how strict the flight substitution is. However, the social benefits of those carbon emissions might fall short of the travel time losses experienced by the passengers. Increased investment to improve rail speeds and intermodal accessibility appears necessary before the substitution policies can be implemented.